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I hate approximately everything about this article, but I'm glad that I took a second look through because this is a decent framework for the-thing-which-he-swe
by orzig 3y ago
I hate approximately everything about this article, but I'm glad that I took a second look through because this is a decent framework for the-thing-which-he-swears-isnt-prompt-engineering:
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* diagnosis
* decomposition
* reframing
* constraint design.
Diagnosis is discovering the problem that AI can solve. This is the human part of knowing that a problem exists. Learning to ask the right questions, look at the different ways that the problem can be seen.
Decomposition is about splitting the big problems into bite-sized ones. Take the problem apart, examine it, and let AI help you determine your findings since it handles data so well. Instead of tackling the biggest problem, take it apart and work on the smaller parts to achieve small successes.
Reframing is about shifting your perspective and seeking new interpretations. Extrapolating and recombining the parts of the problem in order to identify the meta components. Perhaps a new way of looking at the problem may find a solution hidden in plain sight.
Constraint design is about setting boundaries for the solution. Knowing what to accomplish, and when to know it is done. Setting the length, style, and description of the audience can help AI understand its mission. But we have to know that first in order to instruct.
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As someone who asks GPT and junior developers for lots of things, there are a lot of similarities. I don't imagine that is going away, at least until we wire LLMs up to a huge amount of rapidly changing, cross-silo context so it could understand "Fix the monitoring that slowed our recognition of yesterday's bug". So being thoughtful isn't going away. The author agrees with that (see above), but doesn't make clear where he draws the boundary between "being thoughful" and "prompt engineering"
- Macha 3y agoThat's just systems analysis though. To call rediscovering that prompt engineering just because you're dealing with AI rather than programmers siloed away from business processes feels a little silly and just being justified to keep the title when as originally formulated by the people who first started using it, it was about learning the "magic words" for a specific LLM
- fnordpiglet 3y agoSee I always saw prompt engineering as the ability to author a prompt that elicits a specific behavior by the LLM, not simply the incantation to make to it say penis or talk like a sailor. The “make the AI be lewd” was a parlor trick, but the art of making it behave the way you want and to get the answers you want at the depth, breadth, and form you need is a skill and one I think isn’t going away in our lifetime. I’d further note that writing to influence humans to your intended response and understanding is a widely studied field by every study with multiple PhD and beyond disciplines associated. We even elect such people to lead us largely through their ability to prompt engineer humans. IMO - Folks seem to be reacting to the term “engineer” in the same way traditional engineers with engineering exams do to software engineers claiming to be engineers despite often graduating from a LAS school or not at all - I have a bunch of PE EE in my family and they treat my claim to be an engineer with extreme scorn.